Inferences about members of kinds: The generics hypothesis

Sangeet Khemlani, Sarah Jane Leslie, Sam Glucksberg

Research output: Contribution to journalArticlepeer-review

29 Scopus citations


People routinely make inferences based on kind membership. For example, if you were told that a particular kind of animal is a tiger, then you would likely infer that it has stripes. Under what conditions are people willing to infer that a member of a given kind has a property? Two hypotheses were examined. The base rate or prevalence hypothesis holds that people rely only on their knowledge of the statistical frequency of a property among its kind to infer whether a member has that property. An alternative is the generics hypothesis, which states that people are influenced by their belief that the relevant generic generalization is true. In other words, if people agree to the generalization, "ducks lay eggs", then they should be willing to make the inference that an arbitrary individual duck lays eggs, despite their knowledge that the majority of ducks do not lay eggs (i.e., juveniles, males, and infertile females). We present data that support the second hypothesis. Rather than being driven solely by beliefs about prevalence, agreement to the relevant generic predicted performance on an inference task beyond estimated prevalence or cue validity. These findings suggest that models of categorization that are based solely on statistical or simple probabilistic principles are incomplete. They also provide support for the idea that generics articulate core conceptual beliefs that guide our interactions with the world.

Original languageEnglish (US)
Pages (from-to)887-900
Number of pages14
JournalLanguage and Cognitive Processes
Issue number6
StatePublished - Jul 2012

All Science Journal Classification (ASJC) codes

  • Experimental and Cognitive Psychology
  • Language and Linguistics
  • Education
  • Linguistics and Language


  • Concepts
  • Default inferences
  • Generics
  • Generics hypothesis
  • Non-monotonic reasoning


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